Minimising total tardiness for the worker assignment scheduling problem in identical parallel-machine models

Abstract

The worker assignment scheduling problem involves both the decisions of job scheduling and worker assignment. In this research, only the performance measure of total tardiness is investigated in the model of identical parallel machines with nonpreemptive jobs. Since the worker assignment scheduling problem in the selected model can be shown to be NP-complete, heuristics have been developed for minimising the total tardiness. The worker assignment scheduling problem is solved in two phases of job scheduling and worker assignment. The SES (SPT, EDD, SLACK) heuristic is used for the phase of job scheduling. For the phase of worker assignment, the largest marginal contribution (LMC) procedure is used to minimise the total tardiness. From the simulation conducted, 88 out of 100 simulated problems yielded optimal solutions while the others also obtained very good results. In conclusion, the heuristics developed have shown very impressive results in both effectiveness and efficiency aspects.

Workforce planning and production scheduling in a reconfigurable manufacturing system facing the COVID-19 pandemic

“…Thus, the number of workers is equal to or greater than the number of machines. In this regard, Hu [24] studied an identical parallel machine scheduling problem to minimize the total tardiness where the processing time of a job depends on the number of allocated workers to the associated machine. He developed a two-phase heuristic method to solve the problem, in which the first phase is related to job scheduling, and the second phase performs worker allocation.…”